A First Course in Statistical Methods addresses a pressing need in the methods course--a shorter text designed for a one-term course. By selecting and revising material from their best-selling two-semester text, An Introduction to Statistical Methods and Data Analysis, Fifth Edition, the authors created an ideal book for a one-term course in statistical methods. Based on the belief that statistics is a thought process tied to the scientific method, the text utilizes a 5-step approach: 1) defining the problem, 2) collecting data, 3) summarizing data, 4) analyzing and interpreting the data, and 5) communicating the results of the analysis.

Benefits:

In order to encourage students with limited mathematical background and ability, the authors have taken great care to ensure that the material presented uses understandable, non-technical descriptions of concepts, without relying solely on formulas.

"Encounters with Real Data" sections appear at the end of appropriate chapters. These sections make use of real data sets compiled by Bruce Trumbo, and taken from his casebook, Learning Statistics with Real Data. These real data sets present relevant, interesting challenges to students, requiring multiple methods for data analysis.

Examples and exercises are taken from various disciplines, appealing to a wide range of students. In addition, the examples and exercises, many of which have been taken from journal articles, newspapers, or the authors' own consulting experiences, have been praised for their practicality and usefulness.

The book makes wide use of graphical displays of data that help students understand data and evaluate critical assumptions.

The authors' approach emphasizes interpretation and analysis of data over computation.

The technology friendly approach allows computers to handle formulas so that students can focus on interpretation and analysis of data. Computer output from popular statistical data analysis packages, including Minitab, SAS, JMP, SPSS, and Stata, appears in the examples and exercises.

A First Course in Statistical Methods addresses a pressing need in the methods course--a shorter text designed for a one-term course. By selecting and revising material from their best-selling two-semester text, An Introduction to Statistical Methods and Data Analysis, Fifth Edition, the authors created an ideal book for a one-term course in statistical methods. Based on the belief that statistics is a thought process tied to the scientific method, the text utilizes a 5-step approach: 1) defining the problem, 2) collecting data, 3) summarizing data, 4) analyzing and interpreting the data, and 5) communicating the results of the analysis.

Benefits:

In order to encourage students with limited mathematical background and ability, the authors have taken great care to ensure that the material presented uses understandable, non-technical descriptions of concepts, without relying solely on formulas.

"Encounters with Real Data" sections appear at the end of appropriate chapters. These sections make use of real data sets compiled by Bruce Trumbo, and taken from his casebook, Learning Statistics with Real Data. These real data sets present relevant, interesting challenges to students, requiring multiple methods for data analysis.

Examples and exercises are taken from various disciplines, appealing to a wide range of students. In addition, the examples and exercises, many of which have been taken from journal articles, newspapers, or the authors' own consulting experiences, have been praised for their practicality and usefulness.

The book makes wide use of graphical displays of data that help students understand data and evaluate critical assumptions.

The authors' approach emphasizes interpretation and analysis of data over computation.

The technology friendly approach allows computers to handle formulas so that students can focus on interpretation and analysis of data. Computer output from popular statistical data analysis packages, including Minitab, SAS, JMP, SPSS, and Stata, appears in the examples and exercises.